Neonatal respiratory distress syndrome (RDS) is the most common respiratory cause of mortality and morbidity among infants in the United States. While RDS is most commonly attributed to a developmental immaturity of pulmonary surfactant production, a genetic mechanism is suggested by studies of twins, ethnicity, gender, and lethal mutations in surfactant-related genes (SFTPB, SFTPC, and ABCA3). Prior research to define the genetic mechanisms underlying neonatal RDS has focused on common genetic variants within single candidate genes and explains only a small proportion of disease heritability. Research in complex adult diseases that reduce reproductive fitness suggests that combinations of rare, highly penetrant variants in multiple genes account for disease heritability. Our laboratory has identified statistical and functional associations of rare variants in surfactant-related genes with neonatal RDS. The goals of this proposal are to identify gene loci with excess, rare, functional variants that statistically account for the missing heritability of RDS and to develop methods to test the biologic mechanisms by which genetic variants disrupt surfactant metabolism. First, we will use next generation sequencing to determine the population-based frequencies of rare genetic variants among five surfactant-related genes (SFTPC, ABCA3, LPCAT, CHPT, and PCYT1B) using 1,116 infant samples obtained from the Missouri Department of Health. Second, we will determine whether excess, rare, functionally disruptive variants in these five genes are overrepresented among infants with RDS compared to infants without RDS in already available DNA samples with informed consent (N=940 infants of African and European descent). Third, we will use cell-based functional assays to investigate the underlying biologic mechanisms of these disruptive variants. This comprehensive research strategy is novel because we will study candidate genes with higher resolution, use software based algorithms to assess variant functionality, use traditional (regression) and novel (Collapsing Methods, BimBam, logic regression) statistical approaches to evaluate variant interactions, and use cell-based assays to study the functionality of identified variants and combinations of variants. The development of cell-based assays will permit mechanistic study of variants identified through statistical associations and provide the basis for the long-term development of diagnostic and therapeutic approaches for affected infants. The combination of my clinical experience, prior didactic and mentored training in genetic epidemiology, and an integrated training plan that allows me to develop skills in the use of surrogate cell systems will enable me to develop into an independent investigator that can bridge statistical observation with functional mechanism and translate these findings into specific therapeutic approaches for infants with RDS.